Dynamic Brain Sources of Visual Evoked Responses

By Scott Makeig, Marissa Westerfield, Tzyy-Ping Jung, S. Enghoff, Jeanne Townsend, Eric Courchesne, Terrence J. Sejnowski. Science, 2002

1,729 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience

View Paper: https://www.semanticscholar.org/paper/46dc79e1a5dd23c64efc29d3d64d50b9085b583e

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In Cognitive Neuroscience

Citations in the corpus

Enhanced detection of artifacts in EEG data using higher-order statistics and independent component analysis (2007, methodology): “minimizing the effects of volume conduction, ICA allows detailed examination of the separate dynamics and dynamic inter-relationships of different cortical areas (Delorme and Makeig, 2003; Makeig et al., 2002).”
Does physical interstimulus variance account for early electrophysiological face sensitive responses in the human brain? Ten lessons on the N170 (2008, background): “Interestingly, it has been proposed that the visual N1 component to simple stimuli can indeed be largely generated by such a phase resetting of EEG ongoing oscillations in the alpha range (Makeig et al., 2002).”
Optimal sustained attention is linked to the spectral content of background EEG activity: greater ongoing tonic alpha (∼10 Hz) power supports successful phasic goal activation (2007, methodology): “3).”
EEG alpha oscillations: the inhibition-timing hypothesis. (2007, background): “…concentration takes place at least in that frequency range that is evident as a dominant ongoing oscillation already during a prestimulus interval (Makeig et al., 2002; Klimesch et al., 2004), (iii) the frequency characteristics of evoked activity (i.e., early ERP components) resemble those of…”
Bridging emotion theory and neurobiology through dynamic systems modeling (2005, background): “Makeig et al. (2002) showed that perceptual ERPs result from the compilation of alpha-band oscillations, synchronized by the triggering effect of a stimulus event.”
Trial-by-Trial Coupling of Concurrent Electroencephalogram and Functional Magnetic Resonance Imaging Identifies the Dynamics of Performance Monitoring (2005, methodology): “To account for this problem, independent component (IC) analysis (ICA) can be applied, a statistical source separation technique suitable for single-trial EEG analysis (Makeig et al., 2002, 2004).”
Phase patterns of neuronal responses reliably discriminate speech in human auditory cortex. (2007, background): “This view is motivated by studies demonstrating that EEG and MEG signals are dominated by stimulus-induced changes in endogenous ongoing brain dynamics rather than by stimulus-evoked events (Makeig et al., 2002; Penny et al., 2002) and importantly, those inherent brain rhythms have been found to hav”
EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. (2004, methodology): “…the biologically plausible sources ICA identifies in EEG data have scalp maps nearly fitting the projection of a single equivalent current dipole (Jung et al., 2001; Makeig et al., 2002), and are therefore quite compatible with the projection to the scalp electrodes of synchronous local field…”
Reward expectation modulates feedback-related negativity and EEG spectra (2007, positive): “Recent findings using this approach have revealed novel insights into task-related cognitive processes beyond what is evident in averaged ERPs (Fell et al., 2004; Makeig et al., 2002; Salinas and Sejnowski, 2001).”
Single-Trial Normalization for Event-Related Spectral Decomposition Reduces Sensitivity to Noisy Trials (2011, background): “Most ERP peaks have been shown to result from a reorganization of the phase of ongoing EEG oscillations (Tallon-Baudry et al., 1996; Delorme et al., 2002; Makeig et al., 2002).”
Beyond ERPs: Oscillatory neuronal dynamics (2012, positive): “Since alpha oscillations are the predominant oscillatory activity in the EEG/MEG, it is believed that the phase-resetting of these oscillations are particularly relevant for producing the ERP (Gruber, Klimesch, Sauseng, & Doppelmayr, 2005; Klimesch et al., 2004; Makeig et al., 2002).”
Spike-phase coding boosts and stabilizes information carried by spatial and temporal spike patterns. (2009, positive): “In addition, the precise timing of slow rhythms can be controlled by sensory stimuli, since the phase of slow rhythms can be reset by the onset of sensory stimuli or by modulatory inputs (Kayser, 2008; Lakatos et al., 2007; Lakatos et al., 2005b; Makeig et al., 2002).”
The Phase of Ongoing EEG Oscillations Predicts Visual Perception (2009, background): “The existence of a relationship between spontaneous EEG alpha phase and the amplitude of subsequent ERPs (Varela et al., 1981; Jansen and Brandt, 1991; Haig and Gordon, 1998; Makeig et al., 2002; Kruglikov and Schiff, 2003; Barry et al., 2004) or the speed of manual responses (Callaway and Yeager, 1”
Independent EEG Sources Are Dipolar (2012, methodology): “of each maximally independent source to the scalp sensors, thereby also greatly simplifying the problem of determining Where in the brain each EEG source signal is generated [12,24].”
Imaging human EEG dynamics using independent component analysis. (2006, background): “One straightforward way to cluster components across subjects is to choose components contributing the most energy to an ERP feature of interest (Makeig et al., 1997, 2002).”
Event-related EEG time-frequency analysis: an overview of measures and an analysis of early gamma band phase locking in schizophrenia. (2008, background): “imental events, leading to transient time- and phase locking of frequency-specific oscillations with respect to an event’s onset on trial after trial.(7,8) These phase-”